Deployment and Upgrade for Railway and Highway Intelligent Due Diligence Reports

Data sources for railway and highway intelligent due diligence include project approval public notices from transportation authorities, operation and

What the Data for This Category Looks Like

Data sources for railway and highway intelligent due diligence include project approval public notices from transportation authorities, operation and maintenance reports from operators, regular inspection records of facilities along the route, and publicly available traffic and passenger flow statistics. Update rhythms vary across data types: infrastructure line data updates less frequently, usually quarterly or annually. Detection data for bridges and tunnels along the route and monthly traffic volume data update more often. Document structures include structured tables of project cost and mileage details, unstructured PDF inspection reports, and real-time operational data pulled via API. Exclusive fields include total line mileage (unit: kilometers), number of bridges (unit: units), annual traffic volume (unit: ten thousand tons). Some documents include metadata fields such as approval document number and construction time.

Constraints Imposed by These Characteristics on Deployment and Upgrade

Multi-source heterogeneous data characteristics require configuring both structured database connections and unstructured file parsing rules during deployment, to prevent incomplete data access. Differentiated update rhythms require adjusting incremental sync trigger intervals during upgrade, to balance real-time performance and resource usage, and prevent excessive server load caused by full synchronization. The specificity of exclusive fields and units requires custom field mapping rules during deployment, to avoid unit confusion or missing fields from the system's default field parsing logic. Cross-version workflow compatibility requirements require retaining adaptation logic for old-version nodes during upgrade, to prevent failure of existing orchestration workflows.

How to Set Configuration Values

Configuration ItemRecommended ValueRationale
PARSE_FILE_TIMEOUT_SECONDS600 secondsLarge PDF inspection reports for railways and highways typically have many pages and require longer parsing times. This setting avoids interrupting the parsing process due to timeout
KNOWLEDGE_BASE_RECALL_LIMITTop 8-12 entriesDue diligence reports need to cover multiple types of information including infrastructure, operation and maintenance, and operations. Too many recalled entries will increase context length, while too few will miss key details
SYNC_INCREMENTAL_INTERVALEvery 6 hoursBalances synchronization requirements for low-frequency infrastructure data and high-frequency traffic volume data, and strikes a balance between real-time performance and resource usage
FIELD_MAPPING_RULESCalibrated based on actual testingRailway and highway data have exclusive fields and units, so custom mapping is required to adapt to the system's default field parsing logic
UPLOAD_FILE_MAX_SIZE2000 MBFull inspection report PDFs for large projects have large file sizes, so upload limits need to be relaxed to support complete document import
WORKFLOW_IMPORT_STRICT_MODEDisabledSupports cross-version import requirements. For example, when importing a workflow from v4.6.7 into v4.8.10, it automatically adapts to old-version node parameters

The parameter values provided on this page are general recommendations to serve as a starting point for configuration. Actual values are affected by material format, data volume, and business rules. Specific issues require case-by-case analysis. It is recommended to test on your own samples before finalizing settings.

Three Common Mistakes

  • Issue: A "node type incompatible" error occurs when importing workflows across versions, with a status code of 400. Cause: Workflow import strict compatibility mode was not disabled. Custom node parameters from version v4.6.7 cannot be recognized by version v4.8.10.
  • Issue: After source code deployment, the mongo container fails to start normally. Logs prompt image pull failure. Cause: No domestic mirror source was configured to accelerate Docker image pulls, or the image tag version does not match the deployment script.
  • Issue: Knowledge base search returns no results in version v4.8.10, with no obvious error logs. Cause: No incremental sync trigger rules were configured, so the latest traffic volume and facility inspection data for railways and highways were not synchronized to the knowledge base.

How to Verify Successful Configuration

  • Run a single-file parsing test, and confirm that parsed fields match the preset FIELD_MAPPING_RULES.
  • Trigger an incremental sync task, and check that sync logs include update records for railway and highway exclusive fields.
  • Import a v4.6.7 workflow into v4.8.10, and confirm all nodes load normally without errors.
  • Initiate a knowledge base search, and confirm that the number of returned results falls within the range configured for KNOWLEDGE_BASE_RECALL_LIMIT.

Question material comes from public community discussions. Configuration values are common starting points and should be measured against your own samples. Verified on 2026-09-14.